We then compare our classifier-to-detector distillation approach with the state-of-the-art detector-to-detector ones, such as KD [1]}, FGFI [2]}, GID [3]} and FKD [4]}. Here, in addition to the compact students used in Section REF , we also report results on the larger students that are commonly used in the literature, i.e., Faster RCNN and RetinaNet with deeper ResNet50 (R50) backbones.
